During the ongoing financial crisis, it has become clear that investing in equities with an eye toward the long-term return premium can lead to substantial periods of drawdown. It makes sense, therefore, to see a renewed interest in products and strategies aimed at trying to capture this premium at a potentially lower risk level. This strategy is not something new; the low volatility phenomenon was described in the early 1990s by Haugen and Baker. More recently we have seen a related but slightly different approach, namely, minimum variance, as described by Clarke, de Silva and Thorley (2006). Not only have managers deployed these strategies, but such is their popularity that we have recently seen these techniques being deployed by benchmark providers and provided as commercially available ETFs.

Although the two concepts are related and share a common goal (a better risk return profile), there are slight nuances in either approach. Low volatility strategies describe the outperformance of stocks with a lower price fluctuation. Minimum variance takes into account correlations between assets and looks at the volatility of the portfolio rather than the individual securities. Rather than selecting stocks with low and potentially shorting securities with a high (idiosyncratic) volatility, minimum variance focuses on constructing generally long-only portfolios in a way that minimizes the absolute risk.

In our latest white paper, we consider minimum variance investing, not as an advocate, but to examine some of the characteristics of these strategies and how they can potentially be blended with traditional passive market cap weighted investing to improve returns.

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One result of the recent credit crisis is an increased focus on CDS spreads as an early indicator of default risk. This focus has led to increased transparency in the CDS market and more readily available information regarding what those markets are saying about a particular issuer’s probability of default.

When CDS spreads widen, it’s a sign from the derivatives market that a company’s probability of default has increased, and equity and fixed income markets should be expected to respond in kind. The question is: how do we efficiently capture and capitalize on that information?

CDS Spreads as an inversely-related leading indicator of price changes during the BP oil crisis. (Click to enlarge.)

An issuer’s CDS spreads, and the recent movements of those spreads, provide quick, valuable information on whether to open or close a position. However, monitoring CDS spreads on an issuer-by-issuer basis can be time consuming and, frankly, inadequate from a risk oversight perspective.

If you’re digging into a company based on major news stories or some recent event, there’s a good chance you’re going to be late to the game, and the information provided by CDS spreads will already be reflected in the equity and fixed income markets. Rather than taking the reactive approach of “What are the CDS markets saying about company X after event Y, and to what degree are we exposed to company X?”, we can try to fully capture the value of movements in CDS spreads as an early indicator with a more proactive question: “What is our exposure to issuers with widening CDS spreads?”

In other words: Assuming I don’t have a clear picture of the credit profile of every company held by my firm, where are the CDS markets indicating significant changes in the probability of default? There are a number of factors to determining what’s a significant movement:

• Percentage or basis point change in spread
• Absolute change or change relative to a benchmark, sector, country, etc.
• Time period for change: one day, one week, one month
• Tenor of spreads: Anywhere from 1-10 year spreads

Once we’ve determined the companies with indications of a significant credit event, we want to know everywhere that we’re exposed to that issuer. A default, or simply an increased probability of default, can affect all asset classes. It’s essential to identify our exposure to every equity share class, ADR, and preferred as well as every bond, option, derivative, or other instrument linked to or issued by that company.

To ensure that we’re able to capture the value of CDS spread movements as an early indicator the analysis should be run as frequently as the data allows (daily if possible). While the amount of data going into such an analysis can be immense, the communication of the results must be concise so that it can be quickly distributed, consumed, and acted upon. For example, it may be best to simply send a list of the 5-10 issuers with indications of increased default risk and market value held to traders and portfolio managers prior to the market open.

FactSet’s Security Exposures can find the largest exposure to widening CDS spreads by market value (Best Buy) and number of positions (Telefonica). (Click to enlarge.)

The same data can be rearranged to show each managers exposure to widening spreads by portfolio. (Click to enlarge.)

If the CDS market is telling you that an issuer has an increased risk of default, there are a number of questions for which you’ll want a quick answer:

• What is our firm’s aggregate market value at risk from all securities linked to that issuer?
• How many portfolios and individual positions do we hold in that issuer’s securities?
• How liquid are those securities and how long would it take to unwind those positions?

With increased transparency into the CDS market, some valuable data points have been added to the risk overseer’s arsenal. Likewise new applications, like FactSet’s Security Exposures Analysis, have been developed specifically for combing through that data and quickly answering the questions posed above. While CDS spreads are considered an early indicator of increased default risk, it doesn’t take long for the non-CDS markets to catch up. Setting up a timely, flexible process which concisely summarizes the relevant data is essential if you wish to stay proactively ahead of the credit events indicated by the CDS market.

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This month, FactSet hosted a series of risk events throughout Asia and Australia. Representatives from Axioma, R-Squared, MSCI, SunGard APT, and Northfield joined us to debate current topics in risk management in six cities. We presented ideas, answered questions, and brought some new information to over 300 individuals representing a huge number of the major superfunds, pension managers, asset managers, and investment houses of the region.

In addition to presentations from all of the risk providers, our own Dr. Steve Greiner spoke about Currency Exposure Hedging and Stress Testing Potential Sovereign Default. The audience was then invited to ask questions to explore the different opinions and approaches of the providers. This lead to some entertaining clashes over the alternative approaches used and the reasoning behind them. I’ve summarized some of the questions here:

Q: How important is it for the risk model used to contain the factors used in the portfolio construction?

The panelists agreed here that the risk model should indeed include the factors that are being over/under-weighted, as without them it will be difficult to understand the inherent risks that these factors bring. This in itself brings an issue, as virtually all of the commercially available risk models have pre-specified factors, so any custom factors would be represented through a combination of those, an issue that had Laurence Wormald of SungardAPT and Jason MacQueen of R-Squared suggesting their own solutions. Nick Wade of Northfield highlighted a secondary function of a risk model in highlighting factors generating risks that perhaps hadn’t been understood or accounted for, not just those that had been built upon.

Q: Should risk models be daily in nature rather than monthly/weekly?

The panelists stressed the different areas that a comparatively simple sounding question does actually cover: use of daily data in models (against annual/quarterly balance sheet items, etc.); short term horizon models (designed for forecast volatilities over days rather than months); daily updates of monthly-built models. Ultimately, Neil Gilfedder of MSCIBarra underlined his belief that full daily updates are more responsive to changing market environments and this was the driving force for the recent changes in their approach. This methodology is already used by Axioma, and as pointed out by Olivier D’Assier, permits rebalancing at the behest of the manager, not dependent upon the update of the model vendor. It was nice to have some areas of agreement!

Q: How relevant are the risk statistics generated by the models at the constituent level?

Universally, all of the speakers agreed that each of the risk models on FactSet are designed to be used at the portfolio level and potentially provide some level of granularity at the sector level, but reviewing risk statistics at the security level can be dubious to say the least. The statistical techniques and estimation errors involved in the construction benefit from large universes and therefore to consider any individual security as being perfectly described can cause confusion and may lead to false conclusions. Large, well-diversified portfolios, benchmarks, and the like can be described accurately through factor models and therefore these should be the prime targets for their use.

The panel questions expanded to include potential data biases (“Is a Wednesday to Wednesday weekly delta better?”), use of forward looking data (e.g., options volatility surface), as well as the challenges of full data estimation (dummy variables for dummies, anyone?), and so the commentary and thoughts were not only entertaining but also very informative to all. I was a spectator at each of the different venues, and while we may have covered several subjects multiple times, the glaring consistency throughout is surely the need for any managers to understand their chosen risk model and its nuances if they are to benefit fully from it.

I would like to recognize the efforts of all the speakers, especially Steve, Jason, Nick, and Laurence who managed all six cities in 12 days and extend thanks to all of the 300+ attendees. Anyone interested in seeing the panel reconvened should look out for information for London in June 2012.

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